Figure 53: The base in the complex plane of a locally lineally convex set in C
2which is not lineally convex (courtesy Hania Uscka-Wehlou).
57. Existence of Continuous Right Inverses to Linear Mappings in Elementary Geometry.
Christer Kiselman
Partner:Erik Melin, Comsol AB, Stockholm
Funding:Christer: UU 2005 — 2006-04-30; Kingdom of Sweden 2006-05-01 — . Erik: UU 2005–2008.
Period:20050908–
Abstract: A linear mapping of a compact convex subset of a finite-dimensional vector space always pos-sesses a right inverse, but may lack a continuous right inverse even if the set is smoothly bounded. Examples showing this are given as well as conditions guaranteeing the existence of a continuous right inverse, also for other sets.
58. Digital Hyperplanes Christer Kiselman
Partner:Adama Arouna Kone, Universite des Sciences, des Techniques et des Technologies de Bamako, USTTB, Bamako I
Funding: Christer: Kingdom of Sweden. Adama: International Science Programme (ISP) 2011–2016;
Universite des Sciences, des Techniques et des Technologies de Bamako, USTTB, Bamako I 2011 — . Period:20100101–
Abstract: Digital planes in all dimensions are studied.The general goal is to generalize to any dimension the results of Kiselman’s 2011 paper in Mathematika (11-1).
59. Mathematical Concepts and their Linguistic Expression in a Multicultural Setting Christer Kiselman
Partner: Christer Kiselman, Adama Arouna Kon ˜A©, Lars Mouwitz, Fanja Rakontondrajao, Amites Rasho, Shiva Samieinia, Xiaoqin Wang; possibly others.
Funding:Hania: Man In The Middle AB (MITM). Christer: Kingdom of Sweden. Adama: Universit ˜A© des Sciences, des Techniques et des Technologies de Bamako. Lars: Kingdom of Sweden. Fanja: Universit ˜A©
d’Antananarivo. Shiva: Stockholm University; The Ruth and Nils-Erik Period:20161201–
Abstract:To study the relation between mathematical concepts and their expression in several languages.
Special attention is devoted to the use of non-native languages.
60. Digital Distance Functions and Distance Transforms Robin Strand, Gunilla Borgefors
Partner:Benedek Nagy - Dept. of Computer Science, Faculty of Informatics, University of Debrecen, Hun-gary; Nicolas Normand, IRCCyN - University of Nantes, France
Funding:TN-Faculty, UU Period:19930901–
Abstract: The distance between any two grid points in a grid is defined by a distance function. In this project, weighted distances have been considered for many years. A generalization of the weighted dis-tances is obtained by using both weights and a neighborhood sequence to define the distance function.
The neighborhood sequence allows the size of the neighborhood to vary along the paths. A manuscript on distance functions based on multiple types of weighted steps combined with neighborhood sequences has been produced in collaboration with Strand, Nagy and Normand. The manuscript holds (mainly theoreti-cal) results on for example metricity and optimal parameters. Figure 54 illustrates the shapes of disks with different number of weights, when the optimization criterion is roundness in the Euclidean sense.
Figure 54: Digital Distance Functions and Distance Transforms
61. Feature Point Descriptors for Image StitchingAnders Hast, Ida-Maria Sintorn, Damian J. Matuszewski, Carolina W¨ahlby Partner:Vironova AB; Dept. of Electronic Computers RSREU, Ryazan, Russia Funding:TN-Faculty; UU; Science for Life Laboratory
Period:20150101–20171130
Abstract: When microscopy images are to be put together to form a larger image than one field of view, images are stitched together based on key point features in the images. Several methods for matching these images exist, but are often general in the sense that they can handle scale and rotation, which are not present in this particular case. Therefore, these methods are like cracking a nut with a sledge hammer, and we have investigated how simpler and therefore more efficient and also faster methods can be developed and applied for solving this task. Several key point descriptors have been investigated that are based on new sampling strategies and also new ways of combining these samples, using for instance elements of the Fourier transform, instead of histograms of gradients etc. A paper describing two versions of fast and simple feature point descriptor with or without rotation invariance was presented at the WSCG conference. This project resulted in the publication: Matuszewski DJ, Hast A, W¨ahlby C, Sintorn I-M (2017) A short feature vector for image matching: The Log-Polar Magnitude feature descriptor. PLoS ONE 12(11): e0188496.
See Figure 55
Figure 55: Feature Point Descriptors for Image Stitching
62. Image Enhancement Based on Energy Minimization
Nataˇsa Sladoje, Joakim Lindblad, Amit Suveer, Ida-Maria Sintorn
Partner:Buda Baji´c, Faculty of Engineering, University of Novi Sad, Serbia; Anindya Gupta, T. J. Seebeck Dept. of Electronics, Tallinn University of Technology, Estonia
Funding:Swedish Governmental Agency for Innovation Systems (VINNOVA); TN-Faculty, UU; Swedish Research Council
Period:
201409—-Abstract: A common approach to solve the ill-posed problem of image restoration is to formulate it as an energy minimization problem. A priori knowledge is, typically, included through a regularization compo-nent. Total variation is among most popular approaches, due to simplicity and generally good performance.
We have studied performance of energy minimization based restoration for enhancing images degraded with blur and different types of noise - Gaussian, Poisson and mixed Poisson-Gaussian. During 2017, our focus was on application of the developed approaches. We have included energy minimization based denoising in a comparative study of performances of different denoising methods on TEM images of Cilia. We have also developed a Deep learning based method for the same task. Results are presented in the publication ”De-noising of Short Exposure Transmission Electron Microscopy Images for Ultrastructural Enhancement”, accepted for the IEEE International Symposium on Biomedical Imaging - ISBI 2018. In addition, we have incorporated deblurring and super-resolution reconstruction in the energy function proposed earlier for cov-erage segmentation and achieved improved segmentation results. We have suggested an improved global optimization scheme which makes the method applicable to blurred and noisy data. We have prepared and submitted a journal publication. See Figure 56.
Figure 56: Image Enhancement Based on Energy Minimization
63. Predictive Modelling of Real Time Video of Outdoor Scenes Captured With a Moving Handheld Cam-era
Nataˇsa Sladoje, Joakim Lindblad
Partner:Joakim Lindblad, Protracer AB, Stockholm
Funding:Swedish Governmental Agency for Innovation Systems (VINNOVA); Protracer AB Period:201510–20170931
Abstract: This project is inspired by the growing market demand for real time matchmoving technologies in sports broadcasting. Matchmoving, also referred to as video tracking or camera tracking, is a technique that allows 3D computer graphics to be inserted into a live broadcast to enhance the visual experience for the viewing audience. The major technological and functional limitation of existing real time matchmoving technology is its reliance on cameras installed on stands and on a known background settings. Within this project, we have explored and developed software for robust predictive modelling (statistical analysis) of real time video of outdoor scenes captured with a moving handheld camera. This is a collaborative project with Topgolf Sweden AB (formerly Protracer AB), the world-leading provider of ball tracking technology.
The outcomes of this project has part in the very successful expansion of the Toptracer product, includ-ing CBS Sports announcinclud-ing their use of Toptracer on 10 holes for every PGA TOUR event durinclud-ing 2018, particularly the tracking of second and third shots wirelessly from the fairway. See Figure 57
Figure 57: Predictive Modelling of Real Time Video of Outdoor Scenes Captured With a Moving Hand-held Camera
64. Regional Orthogonal Moments for Texture Analysis Ida-Maria Sintorn, Carolina W¨ahlby
Partner:Vironova AB; Sven Nelander, Dept. of Immunology, Genetics and Pathology, UU Funding:Swedish Research Council
Period:
201501—-Abstract: The purpose of this project is to investigate and systematically characterize a novel approach for texture analysis, which we have termed Regional Orthogonal Moments (ROMs). The idea is to com-bine the descriptive strength and compact information representation of orthogonal moments with the well-established local filtering approach for texture analysis. We will explore ROMs and quantitative texture descriptors derived from the ROM filter responses, and characterize them with special consideration to noise, rotation, contrast, scale robustness, and generalization performance, important factors in applications with natural images. In order to do this we will utilize and expand available image texture datasets and adapt machine learning methods for microscopy image prerequisites. The two main applications for which we will validate the ROM texture analysis framework are viral pathogen detection and identification in MiniTEM images, and glioblastoma phenotyping of patient specific cancer stem cell cultures for disease modeling and personalized treatment. During 2016, a paper comparing and evaluating several ROM filter banks on a number of different texture datasets was submitted and is awaiting the review response.
65. Distance Measures Between Images Based on Spatial and Intensity Information, with Applications in Biomedical Image Processing
Johan ¨Ofverstedt, Nataˇsa Sladoje, Joakim Lindblad Partner:Ida-Maria Sintorn, Vironova AB
Funding:Swedish Governmental Agency for Innovation Systems (VINNOVA), TN-Faculty Period:20170101–
Abstract: Many approaches to solving fundamental image analysis problems, such as template matching, image registration, classification and image retrieval are based on some numeric measure of distance (or similarity) between images. This project is focused on a family of such distance measures which are based on the combination of intensity and spatial information. We have studied how to extend the measures from scalar-valued representations to information-rich hybrid object representations. This has resulted in a M.Sc.
thesis titled ”Similarity of Hybrid Object Representations With Applications in Object Recognition and Classification”, a conference paper ”Distance Between Vector-Valued Fuzzy Sets Based on Intersection De-composition with Applications in Object Detection” presented at the ISMM conference in Paris, France, in May 2017, and a conference paper ”Distance Between Vector-valued Representations of Objects in Images with Application in Object Detection and Classification” presented at the IWCIA conference in Plovdiv, Bulgaria, in June 2017. A biomedical application on which we evaluate the developed methods is template matching-based detection of cilia in TEM. We have shown promising performance compared to the com-mon pixel-based measures such as normalized cross-correlation. We are extending the approach towards affine image registration. See Figure 58.
Figure 58: Distance Measures Between Images Based on Spatial and Intensity Information, with Appli-cations in Biomedical Image Processing
66. The Mimimum Barrier Distance Robin Strand, Filip Malmberg
Partner:Punam K. Saha, Dept. of Electrical and Computer Engineering and Dept. of Radiology, University of Iowa, IA, USA; Krzysztof C. Ciesielski, Dept. of Mathematics, West Virginia University, Morgantown, WV, USA; Dept. of Radiology, MIPG, University of Pennsylvania, PA, USA; Stan Sclaroff, Dept. of Com-puter Science, Boston University, USA; Jianming Zhang, Adobe Research, San Jose, USA
Funding:TN-Faculty, UU Period:20110300–
Abstract: This project studies the minimum barrier distance (MBD), given by the difference between the maximum and minimum values that has to be passed to go from one point to another. Theoretical properties as well as efficient computational solutions for the MBD have been developed. During 2017, two papers related to the BMD were presented at the international conference on Discrete Geometry for Computer Im-agery in Vienna. The first paper presented a summary and overview of previous research in this area. The second paper introduced a related distance function, the Boolean Map Distance (BMD). During the year, Filip Malmberg also visited Stan Sclaroff in Boston, to collaborate on further development of the BMD. See Figure 59.
Figure 59: The Mimimum Barrier Distance
67. Skeletonization Gunilla Borgefors
Partner:Punam Saha-Dept. of Electrical and Computer Engineering and Dept. of Radiology, University of Iowa, Iowa City, USA, Gabriella Sanniti di Baja-Institute for high performance computing and networking, CNR, Naples Italy
Funding:UU Period:20131001–
Abstract: Skeletonization has been a useful tool for many different image analysis and manipulation tasks since its inception fifty years ago. The purpose of this project is to collect information about the many different skeletonization methods that have been invented and to spread the knowledge about them and their usefulness. In 2016 Saha and Borgefors edited a Special Issue of Pattern Recognition Letters on the current state-of-the-art of skeletonization theory and applications, including a review Chapter. This year the book
´’Skeletonization
textendash Theory, Methods, and Applications
prime edited by Saha, Borgefors, and Sanniti di Baja was published by Associated press (see Section 6.1). It includes extended and updated version of the special issue, completely new contributions, and an extended survey chapter. See Figure 60.